Of supranodes and socialwashing: network theory and the responsible innovation of social media platforms

Social media networks are expanding rapidly, increasing the spread and scale of information diffusion. Researchers have highlighted distinguishing features of social media network platforms: network structure transparency, public self-monitored digital profiles, homogenized network connections, and node-created digital content. These features, while adding utility to social media platform providers and users, can also be exploited to manipulate users' behavior and overall network outcomes. This paper posits the importance of network theory as critical foundational "laws" upon which the responsible innovation of social media can be built to minimize such manipulation, how such theory can be used to predict the potential impacts of new network innovations, and the resulting difficulty this framing suggests for self-governance on the part of platform providers. Through a case study analysis of Russian social media interference in the 2016 U.S. presidential election, the value of a network theoretic lens is highlighted. The concept of "supranodes", social media nodes empowered via theoretical knowledge and network awareness to socially engineer network structures and outcomes, is developed and the network theoretic features they exploit discussed.